www.c3dc.fr Pier erre Al Alliez ez, Inria Sophia Antipolis Antho - PowerPoint PPT Presentation

A cloud computing platform for 3D scanning, documentation, preservation and dissemination of cultural heritage. www.c3dc.fr Pier erre Al Alliez ez, Inria Sophia Antipolis Antho hony ny Pa Pamart rt, MAP/CNRS

Partners

Culture 3D Cloud An i ima mage ge-base sed m model deling c g cloud ud co comput puting w web s eb ser ervice : : • Dedicated to CH community Versatile (scale, typologies, density) • • Provide high-density and accurate output • Open-source based (MicMac, CGAL,…) • User-friendly

Context Limits o s of cur urren ent pr practices • Requires highly specialized skills (still true for data acquisition) Heterogeneous results depending on software solutions • and practices (trial and error) Remondino, Fabio, et al. "State of the art in high density image matching." The Photogrammetric Record 29.146 (2014): 144-166. • Challeng enge: facilitate adoption of 3D digitization for routine practice

Objectives Digiti tizati tion : : toward d democrati tizati ation • Large use of digital camera • Widespread expert knowledge in image-based modeling • Enabling non-expert end-users to perform 3D digitization 1. Acquisition 4. Online 2. Automatic 3. Storage and settings and visualization remote sharing protocols computing

Culture 3D Cloud Cloud c ud computing ng : : - Digitization: extraordinary computing power (thousands of CPUs) - Storage: continuously growing containers - Diffusion : multi-support - Host in TGIR HumaNum 4 simultaneous users (8cores2.7Ghz/64GbRAM/80Gb)

Scope In progress Implemented

Platform

3D Digitization [WP l P lead ader: r: Liv ivio io de L Luca] 3D Digitization

A Modular Pipeline Acquisition : Settings : Type : Dataset: Processing (MicMac) : • Protocol • EXIF • Linear • Simple • Best and robust • Overlap • Exposure • Circular • Complex strategy • Minimum • White-balance • Random requirements

Automatic data processing Dense matching mode: • Modular - Epipolar (finest) (updated and evolutive) - Multistereo (faster) • Density: • Adaptive - High (1pt/ 4px) (specificities of dataset) - Medium (1pt/ 16px) • Robust - Low (1pt/ 64px) • Robust alignment (optimization and auto-correction) • Demanding calibration model • Automatic initial calibration • Presets • Adaptation to image size • Adaptation to dataset size • Detection of file extension

Examples 6 • Strategy: • Simple • Random • Stereo • Medium • 2 ,5 M points • PLY : 6 7 MB

Examples 6 26 • Strategy: • Complex • Circular • Stereo • Medium • 1 4 ,2 M points • PLY : 3 6 8 MB

Examples 6 25 • Strategy: • Complex • Random • Stereo • High • 5 M points • PLY : 1 4 2 MB

Examples 6 56 • Strategy: • Complex • Circular • Multiview • Medium • 5 ,3 M points • PLY : 1 4 5 MB

Surface Reconstruction Pre -pro c e ssing Re c o nstruc tio n Po st-pro c e ssing Input Output Dense 3D point set Surface mesh Colors 16

Design Choices Generic & modular -> Open source libraries 17

Design Choices Interoperability 18

Example Use Case

6 26 Protocol: • Complex • Circular • Stereo • Medium • 14,2M de de points • PLY : : 368m 368mo

Raw point set 7M points

After denoising & smoothing

Reconstructed surface 29M triangles

Hole filling

Simplified mesh 908k triangles

Simplified mesh 226 000 triangles

Simplified mesh 56 000 triangles

Simplified mesh 7 300 triangles

Conclusion • Affordable service for non- expert users (but data acquisition…) • High computation ressources accessible online • High density and accuracy guaranteed (if correct input data…) • Coming soon : multifocal, c3dc-support@map.cnrs.fr fisheye, UAV